RD Performance. \( \) 
Fig. REF  demonstrates the RD performance of different methods on three datasets, using PSNR and MS-SSIM metrics respectively. The proposed model with 9 variable rates is compared with well-known compression standards (e.g., H. 264 [1]} and H. 265 [2]}) and learned video compression methods (e.g., Wu's [3]}, DVC [4]}, Habibian's [5]}, HLVC [6]}, Agustsson's [7]}). RD curves of Wu's, DVC, and HLVC are from the release in their GitHub, and RD curves of Agustsson's and Habibian's are obtained from the authors. Methods of Wu's and HLVC are designed for B-frame video compression, which is generally better than the P-frame compression because more reference frames are used. Fig. REF  illustrates that the proposed model performs significantly better than other methods under the metric of MS-SSIM, saving 11.10%, 24.52%, 31.43%, 37.02%, 55.86% bits (bits-saving is all measured by BDBR [8]}) compared with Agustsson's, HLVC, Habibian's, DVC and Wu's on the UVG dataset, respectively. In terms of PSNR, the RD performance of the proposed model is better than that of the other learned methods on UVG/MCL-JCV datasets and is competitive to that of H.265. The lower-right figure in Fig. REF  reveals that the RD performance of the proposed model is slightly worse than that of other learned methods on HEVC Class B dataset in terms of PSNR.
